Agent-Driven Software Engineering
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Narrated by:
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Virtual Voice
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By:
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Ajit Singh
This title uses virtual voice narration
Virtual voice is computer-generated narration for audiobooks.
Key Features:
1. Beginner to Advanced Trajectory: The book follows a logical progression, starting with fundamental definitions and gradually moving to advanced topics like LLM-powered agents and AIOps, making it suitable for a wide range of learners.
2. Hands-On Practical Approach: Almost every chapter includes dedicated "Hands-On Lab" sections, providing practical exercises and code snippets to reinforce theoretical concepts.
3. Real-World Case Studies: In-depth case studies on topics like autonomous supply chain management, smart grids, and automated testing provide context and demonstrate the power of ADSE in solving real-world problems.
4. Complete DIY Capstone Project: The final chapter guides the reader step-by-step through building a complete, working multi-agent system, including fully explained source code, bridging the gap between learning and real-world implementation.
5. Focus on Modern Tools & Frameworks: The book covers modern, relevant agent development platforms and libraries (e.g., JADE, LangChain, Autogen concepts), ensuring students learn skills that are immediately applicable in the industry.
6. Simplest Possible Examples: We believe in the power of simplicity. Every concept is introduced with the easiest and most intuitive example possible before exploring more complex scenarios.
7. Comprehensive Coverage: The book covers the entire lifecycle of agent-based systems, including design, architecture, implementation, deployment, testing, and ethical governance.
To Whom This Book is For:
1. B.Tech/M.Tech Computer Science Students: An ideal primary textbook for courses on Artificial Intelligence, Software Engineering, Multi-Agent Systems, and Distributed Systems.
2. Software Developers and Architects: A practical guide for professionals looking to incorporate agent-based designs and AI-driven automation into their projects.
3. AI and Machine Learning Enthusiasts: A perfect resource for those who want to understand how to operationalize AI models as autonomous agents within larger software ecosystems.
4. Academic Researchers: A consolidated reference on the principles, methodologies, and future directions of Agent-Driven Software Engineering.
The book's philosophy is rooted in clarity, practicality, and relevance. It is meticulously structured to cater to both beginners with no prior knowledge of agent systems and advanced learners seeking to explore cutting-edge topics. The content is presented in a lucid, easy-to-understand manner, breaking down complex theories into digestible concepts supported by simple, real-life examples and illustrations.
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